---
tags:
- image-classification
- pytorch
- huggingpics
metrics:
- accuracy

model-index:
- name: gender_vender
  results:
  - task:
      name: Image Classification
      type: image-classification
    metrics:
      - name: Accuracy
        type: accuracy
        value: 0.9375
---

# gender_vender

The difference between this and usual classifiers is, it is not limited to Man and woman. Rather, if you pass a chart, it would not classify as man or woman unlike other classifiers.

Create your own image classifier for **anything** by running [the demo on Google Colab](https://colab.research.google.com/github/nateraw/huggingpics/blob/main/HuggingPics.ipynb).

Report any issues with the demo at the [github repo](https://github.com/nateraw/huggingpics).


## Example Images


#### man

![man](images/man.jpg)

#### random things 

![random things ](images/random_things_.jpg)

#### woman 

![woman ](images/woman_.jpg)